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Method: Integration of high-throughput proteomic data and complementary omics layers with PriOmics
- Robin Kosch,
- Katharina Limm,
- Annette M. Staiger,
- Nadine S. Kurz,
- Nicole Seifert,
- Bence Oláh,
- Stefan Solbrig,
- Viola Poeschel,
- Gerhard Held,
- Marita Ziepert,
- Norbert Schmitz,
- Emil Chteinberg,
- Reiner Siebert,
- Rainer Spang,
- Helena U. Zacharias,
- German Ott,
- Peter J. Oefner,
- and Michael Altenbuchinger
Genome Res. January 2026 36: 197-213; Published in Advance November 18, 2025, doi:10.1101/gr.279487.124
...lymphoma (DLBCL) data set in which we integrate SWATH-MS-based proteomics with transcriptomic and phenotypic data.State-of-the-art proteomic approaches such as liquid chromatography coupled to quadrupole-time of flight tandem mass spectrometry (LC-QTOF-MS/MS) facilitate the high-throughput characterization...
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Method: A high-throughput screening method for selecting feature SNPs to evaluate breed diversity and infer ancestry
- Meilin Zhang,
- Heng Du,
- Yu Zhang,
- Yue Zhuo,
- Zhen Liu,
- Yahui Xue,
- Lei Zhou,
- Sixuan Zhou,
- Wanying Li,
- and Jian-Feng Liu
Genome Res. August 2025 35: 1875-1886; Published in Advance July 15, 2025, doi:10.1101/gr.280176.124
..., adapted to specific local environments and production systems, resulting in abundant breed diversity (Scherf 2000). Especially after an initial pulse during the early Holocene, animal domestication became increasingly frequent, leading to the integration of numerous species into human environments...
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Method: Label-free selection of marker genes in single-cell and spatial transcriptomics with geneCover
- An Wang,
- Stephanie Hicks,
- Donald Geman,
- and Laurent Younes
Genome Res. December 2025 35: 2744-2755; Published in Advance November 12, 2025, doi:10.1101/gr.280539.125
...) Differentially expressed geneCover markers for geneCover clusters 10, 11, and 12. (F) Four graph-based clusters provided by 10x Genomics with the lowest cell abundance. (G) Comparison of geneCover and geneBasis in resolving rare spatial organization in the mouse brain.Whereas all methods manage to identify...
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Method: Polyomino reconstructs spatial transcriptomic profiles with single-cell resolution via a region-allocation method
- Quanyou Cai,
- Lihui Lin,
- Xin Liu,
- and Jiekai Chen
Genome Res. November 2025 35: 2513-2526; Published in Advance October 22, 2025, doi:10.1101/gr.280532.125
...the significantly lower number of bins compared to spatial voxels, this approach reduces the computational parameters necessary for calculating the cell–cell mapping probability. Consequently, Polyomino is effective for integrating large data sets. Next, within each bin, Polyomino pairs the single cell...
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Method: Spatial Cellular Networks from omics data with SpaCeNet
- Stefan Schrod,
- Niklas Lück,
- Robert Lohmayer,
- Stefan Solbrig,
- Dennis Völkl,
- Tina Wipfler,
- Katherine H. Shutta,
- Marouen Ben Guebila,
- Andreas Schäfer,
- Tim Beißbarth,
- Helena U. Zacharias,
- Peter J. Oefner,
- John Quackenbush,
- and Michael Altenbuchinger
Genome Res. September 2024 34: 1371-1383; Published in Advance September 4, 2024, doi:10.1101/gr.279125.124
...spatial transcriptomics dataFinally, we illustrate that SpaCeNet can deal with high-throughput data, capturing hundreds or even thousands of variables and measurements for tens of thousands of cells. In Chen et al. (2022), the mouse organogenesis spatiotemporal transcriptomic atlas (MOSTA) was generated...
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Method: CRISPR-Cas9-based repeat depletion for high-throughput genotyping of complex plant genomes
- Marzia Rossato,
- Luca Marcolungo,
- Luca De Antoni,
- Giulia Lopatriello,
- Elisa Bellucci,
- Gaia Cortinovis,
- Giulia Frascarelli,
- Laura Nanni,
- Elena Bitocchi,
- Valerio Di Vittori,
- Leonardo Vincenzi,
- Filippo Lucchini,
- Kirstin E. Bett,
- Larissa Ramsay,
- David James Konkin,
- Massimo Delledonne,
- and Roberto Papa
Genome Res. May 2023 33: 787-797; Published in Advance May 1, 2023, doi:10.1101/gr.277628.122
...CRISPR-Cas9-based repeat depletion for high-throughput genotyping of complex plant s Marzia Rossato1,2,6, Luca Marcolungo1,6, Luca De Antoni1, Giulia Lopatriello1, Elisa Bellucci3, Gaia Cortinovis3, Giulia Frascarelli3, Laura Nanni3, Elena Bitocchi3, Valerio Di Vittori3, Leonardo Vincenzi1, Filippo...
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Method: High-resolution spatial transcriptomics in fixed tissue using a cost-effective PCL-seq workflow
- Xue Dong,
- Mengzhu Hu,
- Xiaonan Cui,
- Wenjian Zhou,
- Jingtao Cai,
- Guangyao Mao,
- and Weiyang Shi
Genome Res. September 2025 35: 2052-2063; Published in Advance August 5, 2025, doi:10.1101/gr.279906.124
...) and Light-seq (Kishi et al. 2022), with comparable, if not better, sensitivity.Future directions for PCL-seq include expanding its applications to multiomics, automating high-throughput analysis, and implementing AI-assisted image processing for improved ROI selection. In multicellular systems, spatially...
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Method: STCC enhances spatial domain detection through consensus clustering of spatial transcriptomics data
- Congcong Hu,
- Nana Wei,
- Jiyuan Yang,
- Hua-Jun Wu,
- and Xiaoqi Zheng
Genome Res. June 2025 35: 1415-1428; Published in Advance May 12, 2025, doi:10.1101/gr.280031.124
...; and Visualization using the plot_trajectory function to generate trajectory maps that integrate pseudotime information with spatial coordinates. Data setsAll data analyzed in this article are available from publicly available data sets. The mouse brain and human breast cancer data sets are collected from 10x...
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Method: Unified integration of spatial transcriptomics across platforms with LLOKI
- Ellie Haber,
- Ajinkya Deshpande,
- Jian Ma,
- and Spencer Krieger
Genome Res. December 2025 35: 2722-2733; Published in Advance November 13, 2025, doi:10.1101/gr.280803.125
..., Pittsburgh, Pennsylvania 15213, USA Corresponding authors: jianma@cs.cmu.edu, skrieger@andrew.cmu.eduAbstractSpatial transcriptomics (ST) has transformed our understanding of tissue architecture and cellular interactions, but integrating ST data across platforms remains challenging due to differences in gene...
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Resource: Integrated single-cell multiome analysis reveals muscle fiber-type gene regulatory circuitry modulated by endurance exercise
- Aliza B. Rubenstein,
- Gregory R. Smith,
- Zidong Zhang,
- Xi Chen,
- Toby L. Chambers,
- Frederique Ruf-Zamojski,
- Natalia Mendelev,
- Wan Sze Cheng,
- Michel Zamojski,
- Mary Anne S. Amper,
- Venugopalan D. Nair,
- Andrew R. Marderstein,
- Stephen B. Montgomery,
- Olga G. Troyanskaya,
- Elena Zaslavsky,
- Todd Trappe,
- Scott Trappe,
- and Stuart C. Sealfon
Genome Res. July 2025 35: 1664-1677; Published in Advance May 20, 2025, doi:10.1101/gr.280051.124
...Zaslavsky1, Todd Trappe4, Scott Trappe4,9 and Stuart C. Sealfon1,9 1Department of Neurology, Icahn School of Medicine at Mount Sinai (ISMMS), New York, New York 10029, USA; 2Lewis-Sigler Institute of Integrative Genomics, Princeton University, Princeton, New Jersey 08544, USA; 3Center for Computational...

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